Computational Generation of Substrate-Specific Molecular Cages
This work addresses the challenge of designing substrate-specific molecular cages for applications in drug delivery and catalysis, but the method is incremental as it builds on existing graph-based approaches.
The paper proposes a method for computationally generating molecular cages that are designed to capture specific substrates, using graph-based modeling and an algorithm that constructs minimal molecular paths connecting binding patterns, enabling the construction of cages with over a hundred atoms.
In this paper, we propose a method to build molecular cages designed to capture a specific substrate. We model a cage as a graph of atoms with coordinates in space, and several constraints on their edges (degree, length and angle). We use a simple method to place binding patterns which are able to interact with certain parts of the substrate. We then propose an algorithm which considers all possible ways of connecting these binding patterns and try to construct the smallest possible molecular paths realizing these connections. We investigate many variants of our method in order to obtain the most efficient algorithm, able to build cages of more than a hundred atoms.